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CHAPTER 6
Internet of Things (IoT) and the Digital
Business Environment: A Standpoint
Inclusive Cyber Space, Cyber Crimes,
and Cybersecurity
ANAND NAYYAR,1 RUDRA RAMESHWAR,2 and ARUN SOLANKI3
1
2Thapar Institute of Engineering and Technology,
L.M. Thapar School of Management, Thapar School of Management,
E-mail: rudrarameshwar@gmail.com
3
E-mail: ymca.arun@gmail.com
ABSTRACT
Internet of Things (IoT) has a strong backbone support via enhanced devel-
opments in the area of RFID, smart sensors, communication technologies,
and internet protocols. The primary objective is to integrate smart sensors
to work collaboratively without any sort of human intervention to deliver
the best of the class applications and services. With the revolution via
Industry 4.0, Smart Phones, Machine Learning, Deep Learning, and Smart
Sensors, in the coming years, IoT is expected to bridge up all diverse tech-
nologies to enable new applications via connecting physical objectives
to make the intelligent decision making. The chapter outlines an in-depth
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overview of IoT-Technical details, enabling technologies followed by an
in-depth technical overview of protocols enabling IoT-device to device
communication. The chapter enlists cybersecurity issues surrounding IoT
to enable researchers and developers to speed up research in these areas
along with an overview of various simulation tools available for carrying
out research on IoT.
6.1 INTRODUCTION
6.1.1 INTERNET OF THINGS (IOT)
Well is quite known to everyone that in modern world advanced sensors
and related devices used in hosting other devices such as mobile phones,
monitors used at hospitals are connected in a closed envelope of cyberspace
or cyber-physical system; simply to measure and monitor time, location of
human beings and automobile movements, machine vibrations, humidity
in the atmosphere, precipitation, and temperature, etc. (Lohr, 2012).
The Internet of Things (Camarinha-Matos et al., 2013) in short, mostly
professional world called IoT, it connes new domain and endlessly
produces data streams across the globe with its geographical impression
or footprints from interconnected mobile devices, laptops, computers,
actuators, sensors, RFID tags, etc. (Michael and Miller, 2013; Van-Den-
Dam, 2013). However, in a broader spectrum, Big Data generated from
these devices categorized in IoT, which contains well-o Spatio-temporal
information-data. Presently in the age of technology development, an
advancement in the area of IoT and Big Data Analytics, Advance Technolo-
gies presents an array of modern applications including better product-line
management, supplementary eectual and appropriate unlawful exami-
nation, enhancing farming yield output (Jiang et al., 2009; Hori et al.,
2010; Xing et al., 2010; Bo and Wang, 2011), and increasing speed of the
expansion of smart cities (Belissent, 2010; Schaers et al., 2011; Gubbi et
al., 2013) with new architecture (Balakrishna, 2012; Mitton et al., 2012;
Theodoridis et al., 2013; Jin et al., 2014), world-class infrastructure and
communication network step-up.
In the age of Social Media and a high-speed internet connection,
various social networks are active such as Facebook, Twitter, LinkedIn;
Blogs generate Big Data, responsible for the transformation of the social
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sciences area in and around. However, during the time of writing, many
social media users, particularly in case of Twitter, users across the globe
roughly or on an average 6000+ tweet per second, fairly which corre-
sponds to 500+ million tweets /day and around 200+ billion tweets/year,
according to internet Live Stats-2016 database. Similarly, the big data
count follows in the case of Facebook, LinkedIn, Blogs, WhatsApp, and
other social media platforms.
Nonetheless, Social Scientists, Economists, Political Scientists, and
other scholars use Big Data mining methods to analyze social variable
and their interactions regarding research parameters in vibrant areas
such as health records, phone logs, government records and other digital
traces (Boyd and Crawford, 2012). Even as such data mining methods
promote governments and social studies (Grimmer, 2015) increases big
data acquaintances, it is still demanding to rapidly haul out spatiotemporal
patterns from big data social aairs too, for example, it helps in the predic-
tion of criminal activity (Hener, 2014) on the continuous evaluation
basis, scrutinize emerging public health threats and provide more eective
intervention (Lampos and Cristianini, 2010; Jalali et al., 2012) solutions to
ongoing threats in the concerned areas.
6.1.2 DIGITAL BUSINESS ENVIRONMENT
Digital business environment is altering customer expectations and
business models. It is changing how businesses converse, conduct, and
network with customers as well as with other business such as partners
and suppliers. It is increasing the pace of business. And it is changing
industries and the competitive landscape through a social web monitoring
system based on IoT, Big Data, Information Framework, Networking
Technologies, and Leveraging Cloud Computing.”Digital business is blur-
ring the digital and physical worlds. According to Forbes, Digital Business
is Everyone’s Business. Moreover, it agreed to support in an exceptional
meeting of person, business strategies, and other belongings that inter-
rupts accessible business models – even those born of the internet and
e-business eras.” According to Jorge Lopez, a ‘distinguished analyst’ with
Gartner, Digital business is shaping the future-and businesses must evolve
their business ecosystems and technology to remain competitive.
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“If digital disruption can be viewed as a wave sweeping over indus-
tries, most are in the crest of that wave or soon will be,” according to
research from HBR, an overwhelming majority (80%) of the executives
in a Harvard Business Review (HBR) study thinks “their industry will be
disrupted” by global digital business trends, according to HBR, competing
in 2020: Winners and Losers in the Digital Economy, April 2017.
“Digital technology platforms are the building blocks for a digital busi-
ness. In case of Gartner’s Top 10 Strategic Technology Trends for 2017,
January 2017, every organization [must] have some mix of digital tech-
nology platforms: Information systems, customer experience, analytics,
and intelligence, the Internet of Things and business ecosystems,” said
the HBR study authors in Gartner. One critical point in keeping pace with
the evolving digital environment is ensuring the evolution of the manage-
ment and transfer of business-critical data. In the digital era, constantly
evolving forms of digital data must be synchronized and shared- and done
so quickly, eciently, and securely-with consumers, partners, and other
businesses.
6.2 BACKGROUND
6.2.1 CYBERSECURITY REGULATIONS IMPROVEMENT
We ought to see a proceeding enhancement within the pertinent regula-
tions as connected to cybersecurity. The fast-moving and dynamic nature
of cybersecurity outpaces regulation which is far too clumsy and slow to
be of any advantage and might really ruin security by building a culture
of compliance with regulations and a wrong sense of security against
enemies who are clever, motivated, and agile.
6.2.2 DATA THEFT TURNING INTO DATA MANIPULATION
We can anticipate seeing attackers changing their strategy from website
hacking and pure data theft to attacking data integrity itself. This sort of
attack, in comparison to a straightforward theft of data, will serve to cause
long-term, reputational harm to people or groups by getting individuals to
question the integrity of the data in question.
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6.3 CYBERSECURITY AND INTERNET OF THINGS (IOT)
6.3.1 CYBERSECURITY AND INTERNET OF THINGS (IOT):
CHALLENGES AND ISSUES
The rapid development of smart IoT devices (Rose et al., 2015) has opened
up a number of ways for hackers to invade user privacy. The IoT is making
our lives easier while leaving us less secure. Whenever a major techno-
logical innovation comes along, hackers find ways to exploit it. The world
of IoT includes a huge variety of wire and wireless devices like smart-
phones, personal computers, PDAs, laptops, tablets, and other handheld
embedded devices. IoT has also been known as Cyber-Physical Systems
(CPS), M2M (Machine to Machine), and Simply Industrial Internet (SII)
and connected devices. The generic topology of the IoT seen in layers to
incorporate the Datacenter, Gateway, IoT Gadgets and Sensors. The IoT
devices used sensors and wireless communication network to communi-
cate with each other and transfer information to the centralized system.
These days the embracing rate of the IoT devices is very high, increas-
ingly gadgets are connected via the internet. In the current scenario, these
devices are targeted by attackers and intruders. A report found that 70% of
the IoT devices are very easy to attack (Hossain et al., 2015) (Figure 6.1).
FIGURE 6.1 (See color insert.) IoT topology.
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There are many critical challenges and issues regarding the security
of IoT devices. This section covers these issues and suggests the prob-
able solution. Generally, IoT has used Perception, Network, Middle, and
Application layer in data transmission and processing (Suo et al., 2012).
Each layer has its own importance.
Network layer transmits the gathered information obtained from the
perception layer. This information is sent by using existing communication
networks like the Internet, Mobile Network, or any other kind of reliable
network (Yang et al., 2012). The middle layer comprises of information
processing systems that take automated activities based on the results of
processed data received from the network layer. This layer also links the
system with the database, which is having information about the collected
data. The middle layer is a service-oriented layer which ensures the same
service type as the connected IoT devices (Khan, 2012). The application
layer is founded on TCP and UDP to solve the communication challenges
and used by various applications like Smart Home, Smart Environment,
Smart Transportation and Smart Hospital, etc. (Rong and Tao, 2013).
The major security goal of IoT is Data Condentiality, Data Integrity,
and Data Availability; whereas Data condentiality ensures that there will
be no outer inference. It ensures that only trusted communication will be
taken place, and no information will be leaked to outsiders. Two steps
verication like Gmail or the encryption process may be used to achieve
data condentiality. These techniques provide authentication to the trusted
user only. In the current trend, biometric verication is used for user
authentication (Miorandi et al., 2012).
During data transmission, data could be accessed or changed by the
intruders or cybercriminals or could be aected by various other aspects
like the crash of a server or an electromagnetic disturbance. Data Integ-
rity ensures that data should not be tampered with during transmission
by intruders, hackers, or cybercriminals (Atzori et al., 2010). Dierent
methods like Checksum and Cyclic Redundancy Check (CRC) are used
to ensure the originality of data. Availability of data to trusted resources
is a major challenge in IoT. IoT protocol ensures that every authenticate
resource will always access the data as required. It may be possible
some entrusted resource wants to access the condential information so
it is necessary to provide rewalls to countermeasure the attacks on the
services like Denial-of-Service (DoS) attack which can deny the avail-
ability of data (Reddy et al., 2017).
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1. Cybersecurity Lacks Control Environment and Tools for IoT
Devices: In cyberspace, commercial products are at high risk. Currently,
there is no up to the mark security measures, and even no tool exists to
remove the existing risk. As the consumer is not aware of this risk, so
consumer demand in the cybersecurity area remains low. Especially in
consumer products as many types of attacks, such as denial-of-service
attacks, do not aect the people who own the equipment. If media or social
sites aware the consumer about risk in cyberspace, then vulnerabilities
might raise consumer awareness of the impacts of inadequate cybersecu-
rity, and with it the demands they make of manufacturers.
There is a need for “trusted IoT label” for IoT products that meet
certain security requirements. This label will be aware of the specication
of IoT product with risk, and it will clearly deliver more energy-ecient
products to the consumer. The government should take some initiative
through legislation and regulation. These rules will decrease the risk of
IoT products. The labeling of IoT Products under these rules places greater
responsibility on the manufacturers and importers of products, and this has
generally worked well (Appazov, 2014). A feasible cybersecurity structure
shall aim at the evolution of the adequate cybersecurity environment for
IoT devices. Therefore, it shall include national and international coopera-
tive eorts to develop standards, methodologies, procedures, and processes
that align policy comprising business, health, entertainment, education,
and technology approaches to address cybersecurity issues (Teplinsky,
2013). The private sector will play as signicant a role in the implementa-
tion of the policy as does the public sector. The policy on cybersecurity
shall be informed by the adequate understanding of the cyber-vulnerability
threat on the part of the policy development.
6.3.2 WHY ATTACKERS WILL CONTINUE TO TARGET CONSUMER
DEVICES?
In the era of the IoT, the smart devices are the part of every aspect of our
lives which include homes, offices, cars, and even our bodies. As internet
upgraded to IP4 to IPv6 and Wi-Fi network advances, IoT is growing at
a very fast speed, and researchers estimate that by 2020, the number of
active wireless connected devices will exceed 40 billion (ABI Research,
2014). As the number of active connected devices increases the chance
of hacking the data will be increased and targeted by the cybercriminals.
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The IoT companies are constantly making smart-devices at low cost to
customers. As a result, companies have to lower down the security of an
IoT device in favor of its cost, size, and low energy consumption. These
devices are different from each other in their application area.
Nowadays, in the market, there are lots of smart-gadgets with poor
security services available to a remote attacker. Consumers never think
that their smart device is not venerable and these devices can be hacked
in a matter of seconds. The large-scale gathering of IoT devices and
user-generated content opens user to the risk of data misuse and abuse. If
proper security measures have not taken then it becomes disasters to the
IoT users. In the basic IoT environment, shows simple information that is
easy to understand for possible vulnerable components.
By analyzing the IoT environment, there is a possibility to dene
possible attack vectors used by attackers. The environment consists of
a basic sensor which collects measurable data. The transmission of data
from the sensor to the server gives many loopholes for attackers. Attackers
used these loopholes and hacked or modify the IoT environment.
This section will cover the loopholes in IoT devices which are used by
attackers to hack the consumer devices:
•Users are not using the secure web/desktop/mobile applications
which can provide proper authentication and authorization.
•Two-step authentications are not used by the IoT device security.
•Hackers used a Cross-Site Scripting (XSS), SQL injection, and
Buffer over Flow (BoF) vulnerabilities to hack the IoT devices.
•Simple passwords like ‘123,’ ‘password,’ the name of the user, date
of birth, etc. lead to hacking of IoT device.
•Not using Captcha to secure IoT devices.
•Brute force attacks are done by the hackers.
•Companies are not providing the security updates including details
on security fixes, the impact of the vulnerability, etc.
•Consumers are not using encryption for communication.
•Vendors or customers are providing sensitive data like name,
phone number, DOB, etc., publicly through different social media
platforms.
•Vendors are not testing the security of IoT devices when new
features are added.
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Following are some proposed solution to overcome the security issues
in IoT devices:
•The user always updates their device security from a trusted source.
•User updates device regularly.
•Users always read the manual and user instructions provided by the
vendor.
•2-way authentication always provides the enhanced security to the
device.
•Use strong, unique, and complex passwords at least 8–20 characters
with a mixture of letters, numbers, and special characters.
•The user always ensures to take backups in a secure place.
•Stop unwanted services used by the devices.
DTH service is one of the examples of IoT device. What happens if
hackers hack the personal information of a user and use this information to
hack the DTH service? There will be a big impact on DTH business which
may lead to the following consequences:
•Customer personal information can be used for social engineering
or any other advanced attacks.
•DTH service may be interrupted.
•The consumer will not trust DTH service providers.
•Consumer account, including recharge money can be lost.
•Data are theft by the hackers, including favorite channels, recording,
etc.
The IoT is forcing many business leaders to reassess their approaches
to cyber risk management.
6.3.3 PROTECTION OF IOT DEVICES IN CYBER SPACE
The first question comes in the consumer mind why we need to protect
IoT device data. The reason is to protect one’s own intellectual property
against other competitors. This is a way of preventing others to compro-
mise one’s own environment and use it for malicious purposes (Sagedhi,
2017). The IoT device security in cyberspace is presented with the triangle.
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This triangle visualizes the essential steps desired to obtain a high level of
security consciousness with IoT devices (Sagedhi, 2017).
The triangle will be visualized from bottom to top i.e., green part is the
target. The rst two gray steps, i.e., meaningfulness/usefulness and func-
tional correctness are the starting point of the journey to a higher security
level. These two levels show that an IoT device with internet without any
security features can have duplicate MACs or IP addresses. The security in
these three steps is like unique passwords; the latest software and rmware
versions secured communication protocol such as HTTPS securing web
front-end and security architecture. These three steps in brown color are the
rst implemented security procedures and therefore they aware consumer.
The next three levels with yellow present a higher level of security imple-
mented in an IoT environment. The practical implementations with these
levels are like swarm attestation, IoT sentinel and the implementation of
automatic vulnerability and attack detection (Figure 6.2).
FIGURE 6.2 (See color insert.) Cybersecurity awareness triangle.
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The top green triangle is the level IoT device should strive to whenever
it is possible and reasonable as well as economically wise.
Within the current situation, there are more IoT gadgets than people
on Earth, engineers, and developers got to embrace a new paradigm for
cybersecurity within the IoT age. The rapid increase of IoT has produced
big data. Smart sensors are gathering statistics, which are used in the
machine learning algorithm and can be used to attract the customers for
any business. The sheer volume of this data generated from IoT devices
is extremely large. This large volume of data is a security threat if it is not
secure. To make it secure, organizations/users have to do the following
things:
•The organization has to prepare an inventory of all IoT usage
because it’s impossible to defend the unknown.
•The user has to change the default user id and password. Attackers
know these platforms and their defaults. The new password should
be strong.
•Passwords should be changed regularly.
•The user should disable unnecessary remote administration and
features.
•Do not allow untrusted access to the device from the Internet.
•Don’t empower universal plug and play on IoT devices.
•Use secure protocols like HTTPS and SSH for communications.
•Include IoT devices in regular vulnerability management
programs.
1. Dening Security Implementation: To secure IoT devices in
cyberspace, it is necessary to nd possible attack vectors. These attack
vectors might be against the IoT environment. Therefore, security admin-
istrator and system administrator need to secure the environment against
the vulnerability of the IoT devices (Palmers, 2013). The methods for
analyzing the environment could be similar to the zero-day vulnerability
analysis (Figure 6.3).
The zero-day attack is a phenomenon that secures computer appli-
ances before the vulnerability is known or patched against the vulnerable
(Salonen, 2017).
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FIGURE 6.3 Security implementation in IoT environment.
6.4 SOLUTIONS AND RECOMMENDATIONS
6.4.1 PROTOCOLS FOR INTERNET OF THINGS (IOT)
Internet of Things (IoT) plays a crucial role in varied application areas like
Industry 4.0, healthcare, transportation, agriculture, autonomous vehicles
and even disaster management. These days, IoT has also started impro-
vising the quality of daily life of human beings by providing portable and
smart gadgets, business operations in terms of logistics and manufacturing
and future smart homes (Suryadevara and Mukhopadhyay, 2018). The
most prominent example is Smart Home, where everything is controlled
via Sensors like Temperature, Air Conditioning, Kitchen Home Appli-
ances, Lighting, Security cameras, and even cleaning via Smart Robotics.
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Seeing the current research interests of various researchers in IoT,
many new protocols are evolving and getting standardized. Internet of
Things (IoT) is expanding to a plethora of applications via hardware
minimization, smart sensors and “Smart Objects,” and many protocols
are evolving to facilitate Machine to Machine communications. Because
of the remote nature and requirement of wireless networking of smart
objects, IoT systems have to cope up with various limitations in terms of
unreliable, intermittent, and low bandwidth connections for network access
(Javed et al., 2018). To facilitate communication between devices, lots of
protocols are proposed for dierent layers of IoT: Data Link, Network
Layer (Routing and Encapsulation), Session Layer, IoT Management and
Security.
Till date, there is no as such properly defined and proposed architecture
for IoT, which is agreed universally. Internet of Things (IoT) architecture
can be three-layer or five-layer (Mashal et al., 2015; Said and Masud,
2013; Wu et al., 2010). The three-layer architecture was proposed in the
early days of IoT research. It contains three main layers: Perception layer,
Network Layer and Application layer. The bottommost layer of IoT archi-
tecture is perception layer, which is primarily responsible for acquiring
information from devices and convert into digital form. The network layer
is primarily responsible for transmitting digital signals over the network
and application layer is responsible for transferring digital signals to varied
applications (Figure 6.4).
• Perception Layer: In the initial stage of Internet of Things (IoT),
the major task of perception layer is to collect all the data from devices or
objects sensed from the environment, i.e., Temperature, Humidity, Gases,
etc. All the sensors operational in sensor network, performs the task of
collecting, computing, processing, and transmitting varied types of data
to the perception layer. The sensors and other objects in IoT, i.e., GPS
Devices, IP Cameras, Actuators all communication among one another via
specialized network technologies like ZigBee, Wi-Fi, and other short-range
communication protocols. IoT connects lots of heterogeneous devices, so
it is highly required to identify and connect every object or thing in a
signicant manner. Latest research technologies like 6LoWPAN are also
used to connect the devices within the network without any hiccup.
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FIGURE 6.4 Three-layers and five-tier architecture for Internet of Things.
(Source: IoT Direct, (2017). All About Internet of Things. Retrieved from: http://iotdirect.
blogspot.com/.)
• Network Layer: It is regarded as backbone for IoT architecture
and transmits all the data from perception layer to the application
layer in a highly secured manner. The network layer is regarded as the
delivery layer to collect all information acquired from perception layer
and deliver to application layer, i.e., Servers, and Application Softwares.
Lots of research is being conducted till date to propose routing protocols,
and sophisticated communication technologies in the network layer to
improvise core network operations. Unique addressing ecient routing
ensures seamless integration of devices comprising an IoT network.
All types of Wired, Wireless Technologies-Wi-Fi, Bluetooth, RFID,
6LoWPAN ensure unique addressing and break-free connectivity in IoT
network.
• Application Layer: The topmost layer of IoT architecture is the
application layer providing a bridge between applications and users.
It provides application-specic services to the end-user. It facilitates
Intelligent IoT based real-time solutions like Remote Health Moni-
toring, Autonomous Transportation, Disaster Monitoring, Industrial
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Manufacturing and many more. This layer handles all the global manage-
ment of IoT applications (Mashal et al., 2015).
The IoT architecture comprising three layers (Perception, Network,
and Application) no doubt have created a strong foundation of IoT, but
it is not sucient enough to accommodate the advanced concepts of
Internet of Things. In order to facilitate, more advanced research, IoT
architecture is facilitated with new architecture comprising ve layers-
Perception, Transport, Processing, Application, and Business layer
(Mashal et al., 2015; Said and Masud, 2013; Wu et al., 2010; Khan et
al., 2012) -
• Transport Layer: It performs the task of sensor data transfer
from perception layer to processing layer and vice versa using network
communication standards like Wi-Fi, LAN, Bluetooth, RFID, NFC, and
6LoWPAN.
• Processing Layer: It is also termed as middleware layer. It
performs the tasks of storing, analyzing, and processing tons of data
acquired from the transport layer. Various ICT technologies, i.e., Big
Data, Cloud Computing, Data Processing Modules all forms processing
layer.
• Business Layer: The entire management of whole IoT ecosystem
is performed by business layer which includes all types of IoT Applica-
tions, models as well as ensuring privacy and security of end-users.
The most basic protocol considered for facilitating all sorts of IoT based
communication operations was TCP/IP, as it is also regarded as a baseline
protocol for doing all sorts of computer network related operations. But
the utilization of IPv6 was restricted in IoT, as all the IoT enabled devices
are low powered and require limited bandwidth. Many Interest groups
have laid their efforts to define some IoT based standards to facilitate the
IoT development like World Wide Web Consortium (W3C), Institute of
Electrical and Electronics Engineers (IEEE), Internet Engineering Task
Force (IETF) and EPC Global.
The following sections highlight various Network Communication
protocols for IoT for various layers-Data Link, Network Layer (Routing +
Encapsulation) and Session Layer Protocols (Salman and Jain, 2015; Silva
et al., 2018) (Figure 6.5).
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FIGURE 6.5 (See color insert.) IoT communication protocols.
The IoT data link layer protocols combine Physical and MAC Layer
protocols. The following are the Data Link Layer protocols for Internet of
Things (IoT):
• IEEE 802.15.4: This protocol was designed by the IEEE 802.15
PAN working group (Kivinen and Kinney, 2017). The protocol was
designed for low-power, short-range, low-bandwidth as well as low-cost
IoT based devices (LAN/MAN Standards Committee, 2003). It species
physical layer and MAC for LR-WPANs. It denes 16 channels ranging
between 2.4 GHz-2.48 GHz, where every change is 2 MHz wide and sepa-
rated by 5 MHz from each other. There are two types of devices supported
by IEEE 802.15.4:
o Fully Functional Device (FFD): For creating, coordinating, and
maintaining the network and communicating with all types of devices in
the network;
o Restricted Functional Device (RFD): Devices have limited
access and can only communicate with the coordinator.
IEEE 802.15.4 was further extended to IEEE 802.15.4e to facilitate
low power communication. The protocol denes the way how a schedule
is executed via the MAC layer, which can either be centralized or
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decentralized. The protocol can facilitate star or peer to peer topologies
(LAN/MAN Standards Committee, 2003). IEEE 802.15.4 facilitates
packet size of 127 bytes and communication speed is restricted to 250
Kbps. There is inbuilt redundancy in IEEE 802.15.4 making the commu-
nication robust, detect losses and retransmission of all packet loss. The
protocol fully supports 16-bit link addresses to decrease the header size,
overloading of communication and memory requirements.
• IEEE 802.11 AH: To facilitate ecient Machine to Machine
communications, a new standard protocol was proposed, i.e., IEEE
802.11ah by IEEE 80211ah task force (Adame et al., 2014). The standard
was facilitated to solve M2M networks requirements like limited power
devices, long transmission range, small data messages, low data rates and
non-critical delay. IEEE 802.11ah operates over unlicensed radio bands
depending on country-wise regulations, i.e., 863–868 MHz in Europe,
902–928 MHz in the US, and 916.5–927.5 MHz in Japan. It makes use
of OFDM-based waveform comprising 32 or 64 carriers and supports
BPSK, QPSK, and 256-QAM modulations. IEEE 802.11ah supports
three types of stations: Trac Indication Map (TIM); non-TIM stations
and unscheduled stations. TIM stations only listen to access points
beacons to transmit or receive data. Non-TIM stations don’t listen to any
sort of beacon for data transmission. They directly negotiate with Access
Points to acquire transmission time allocated in a Periodic Restricted
Access Window (PRAW).
• WirelessHART: It is IoT data link protocol based on Open
Systems Interconnection model (OSI) and adopts IEEE 802.15.4–2006
standard as physical layer, and uses Time Division Multiple Access
(TDMA) in MAC for channel access and reducing collisions (Hassan et
al., 2017). WirelessHART, globally operates on standard 2.4 GHZ ISM
bank using 15 dierent channels, i.e., 11–26. It encrypts messages and
ascertains integrity to make reliable data transmission. Supports mesh,
star, or cluster topology to facilitate reliable communication as compared
to Wi-Fi especially in industrial environments. It employs redundant
routing at network layer. WirelessHART includes features like: Self-
organization, robust, Simple Implementation, and Interoperability with
other HART devices, highly energy-ecient, scalable, and self – healing
(Figure 6.6).
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FIGURE 6.6 (See color insert.) WirelessHART working.
(Source: ABB, (2018). WirelessHART Information and FAQs. Retrieved from: https://
new.abb.com/products/measurement-products/wireless-products-and-solutions/highlights/
wirelesshart-information-and-faqs.)
• Z-Wave: This was designed and developed by Zensys in Denmark,
is a low-power MAC protocol based on ZigBee for home automation
and was used for IoT based communication especially for smart homes
(Alliance, 2013, 2015; Said and Masud, 2013; Wu et al., 2010). Z-Wave
operates at 908.42 MHz in the US and supports MESH topology. It can
support up to 232 nodes and supports interoperable operations. It makes
use of GFSK and Manchester channel encoding. In a Z-Wave network, the
three main devices are required to comprise a network-Central Station,
Network Controller and End-user devices. Every Z-Wave network
has unique Network ID and every device has Node ID. The Network
ID remains common for all nodes to associate with 1 Z-Wave logical
network. It’s 4 Bytes in size and nodes with dierent Network ID’s can’t
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communicate among each other. Node ID is unique for end-user device
and is only 1-byte of size. Z-Wave supports mesh topology with primary
and secondary controllers (Figure 6.7).
FIGURE 6.7 (See color insert.) Z-wave network.
(Source: SmarterHOME, (2016). Hierarchy of the Z-Wave System. Retrieved from: https://
smarterhome.sk/en/blog/hierarchy-of-the-z-wave-system_39.html.)
• Bluetooth Low Energy (BLE): It also termed as “Bluetooth Smart”
is part of Bluetooth 4.0 specication (Panwar and Misra, 2017; Tosi et al.,
2017). It is a short-range communication protocol and is widely adapted
in-vehicle networking as well as Machine to Machine communication.
BLE is regarded as a best alternative wireless solution as compared to
existing standards like IEEE 802.11b, ZigBee, ANT+ and Bluetooth 3.0.
It operates in standard 2.4 GHz ISM band ranging from 2.4–2.5 GHz and
is divided into 40 channels having frequencies 2402 + k x2 MHz, where
k = 0, 1, 2, 3…39. It makes use of CSMA/CA for all sorts of collision
detection and ACK for reliable message transmission. Its basic network
comprises of Master and Slave called “Piconet.”
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• HomePlug: HomePlug AV is IoT based data link protocol designed
by HomePlug Powerline Alliance especially for home automation prod-
ucts (Homeplug Alliance Kit, 2018). It operates at speed of 200 Mbps
and frequency range of 2 to 28 MHz. HomePlug Power line Alliance has
designed three main specications: HomePlug AV, HomePlug Green PHY,
and HomePlug AV2.
o HomePlug 1.0: It was the rst HomePlug specication with a
speed of 14 Mbps. It makes use of CSMA/CA to transport data from 46 to
1500 bytes long from encapsulated IEEE 802.3 frames as MAC Service
Data Units.
o HomePlug AV: It was designed for applications like HDTV and
VoIP. It operates at speed of 200 Mbps in Physical Layer and 80 Mbps in
MAC Later. It uses OFDM carriers spaced at 24.414 kHz, with carriers
from 2 to 20 MHz.
o HomePlug AV2: It is based on IEEE 1901 standard and fully
interoperable with HomePlug AV and HomePlug Green PHY devices. It
supports PHY rates of 1300 Mbps with full MIMO. It was designed for
emerging applications for consumers like HDTV, Online Gaming, Home
Storage Systems, and VoIP. It oers 1 Gbps speed at Physical Layer and
600 Mbps at MAC Layer.
o HomePlug Green PHY: It was basically proposed for home appli-
ance connectivity like HVAC (Heating, Ventilation, and Air Conditioning)
as well as Smart Meters to facilitate smart grid applications with data
transmission speed of 10 Mbps. HomePlug Green PHY is designed for
low power, cheap cost and small devices facilitate reliable connectivity
during data transmission.
• ITU-T G.9959: G.9959 is MAC layer protocol proposed by
International Telecommunication Unit (ITU) especially for low-cost,
bandwidth, and reliable wireless communication of IoT based devices
(Gomez et al., 2017). G.9959 based networks operate mostly in unli-
censed frequency bands depending on the countries, i.e., US-908.4
MHz, 860.4 MHz in Europe at data rates ranging from 9.6 Kbps to 100
Kbps. G.9959 networks has two dissimilar nodes: Control Nodes and
End Device nodes. All the commands are initiated by control nodes and
these commands are executed by end-device nodes. G.9959 networks,
supports mesh topology and protocol supports max 4 hops between end
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nodes and max 232 nodes in a single network. The average communica-
tion distance between two nodes can be 100 feet with throughput of 40
Kbps.
• DASH7: DASH7 Alliance Protocol is wireless protocol originated
from ISO 18000–7, an active RFID standard and operates on dierent
ISM bands, i.e., 433, 868 and 915 MHz (Ayoub et al., 2018; Weyn et
al., 2013, 2015). It was designed especially for IoT device to device
communication. It species all layers of the OSI model, making it very
easy to implement. DASH7 protocol is highly scalable, supports long-
range wireless communication in encrypted format and supports higher
data rate. It is based on Master/Slave architecture and is highly suitable
for lightweight and transitive trac. DASH7 protocol has 4 classes of
devices-Blinker Device-Simplex device, can perform only data trans-
mission but cannot act as receiver; Endpoint-A low power device that
can perform both roles of data transmission and receiving. As the device
supports wake-up events which gives the device the capability to receive
a request and response can be transmitted; Gateway-connects DASH7
network to outside network; Sub controller-makes use of wake on scan
cycles like typical endpoint devices. DASH7 has two foreground network
protocols: D7A Network Protocol (D7ANP) and D7A DataStream
Protocol (D7ADP).
• DECT/ULE Protocol: DECT (Digital Enhanced Cordless Tele-
communications/Ultra Low Energy) is a wireless communication universal
European standard designed for Sensor Communications and Smart home
automation (Das and Havinga, 2012; Gomez and Paradells, 2010). The
main features of DECT/ULE are being ultra-low-power and consume
less energy as compared to 802.11 standards and have wider coverage
range as compared to IEEE 802.15 and BLE. DECT/ULE follows star
topology, i.e., all devices are connected to each other, and any device can
communicate with any device. DECT/ULE support FDMA, TDMA, and
time division multiplexing and faceless issues with regard to interferences
and collisions.
The main task of Network layer protocols is to route the packets from
one IoT device to another, i.e., from source IoT device to destination IoT
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device. Network layer protocols are further categorized into two catego-
ries: Routing Protocols and Encapsulation Protocols. The following are
the Network Layer Routing Protocols:
• RPL (Routing Protocol for Low-Power and Lossy Networks):
IETF Routing Over Low-power and Lossy links (ROLL) working group
proposed a new distance vector protocol for IoT networks based on IPv6
for resource-constrained nodes called RPL (Winter, 2012; Vasseur, 2011).
It was primarily designed to perform minimum routing via constructing a
robust topology over lossy links. All sorts of network models like Point to
Point, Point to Multipoint and Multipoint to point are supported by RPL
protocol. RPL protocol constructs Destination Oriented Directed Acyclic
Graph (DODAG) which demonstrates all the nodes routing directions. In
DODAG, every node has complete information regarding its parent node,
but no information regarding child nodes. When a node wants to transmit
a message, it sends Destination Advertisement Object (DAO) to its parent
nodes, it is transmitted to the Root node and the root nodes transmit is
based on the destination node. If a new node wants to join the existing
network, it transmits a DODAG Information Solicitation (DIS) message
and the acknowledgment is sent by the root node via acknowledgment
message called DAO-ACk. In the entire network, the only root node has
complete information of DODAG, so all communications can only take
place via the root node.
• CORPL or Cognitive RPL Protocol: This was proposed for
Cognitive Radio Enabled AMI Networks (Aijaz et al., 2015). The protocol
upgrades the conventional RPL protocol to solve dierent routing issues
in Cognitive radio environments by securing primary users as well as
fullling utility prerequisites of the auxiliary network. In order to solve
routing issues, CORPL protocol makes use of opportunistic forwarding
approach to route the packets by making use of multiple forwarder nodes
and implementing a coordinating scheme to choose the best possible next
hop to forward the packet. The approach enhances overall throughput,
reduces end-to-end delay and brings overall reliability in the network. The
two techniques are utilized by CORPL for enhancing performance in the
network because of spectrum sensing. In the rst technique, the perfor-
mance is improvised via collecting sensing schedule information of all
the neighboring nodes. The second technique improvises the performance
by reducing the sensing time of spectrum. The performance evaluation
of CORPL protocol was done in MATLAB with square region of side
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1000 meters which is occupied by 9 PU transmitters and results state that
CORPL protocol has enhanced network reliability by reducing interfer-
ences by up to 50% and also reduced the deadline violation probability of
delay-sensitive trac.
• CARP Protocol: CARP (Channel Aware Routing Protocol) is
a multi-hop routing protocol designed for Underwater WSN networks
(Basagni et al., 2015). Highly ecient for IoT as only small data size
packets are transmitted. The protocol takes into consideration the Link
Quality, which was calculated on the basis of previous network transmis-
sions from neighboring nodes to determine the forwarding nodes. CARP
Protocol operates as:
o Network Initialization: In this, a source node transmits a HELLO
packet in the network which contains the UNIQUE ID of the node as well
as Hop Count. When the packet is received, every node checks hop count
variable, whether greater than the hop count carried by packet by 1+ value.
If it is greater, the value is updated and the packet is transmitted otherwise
dropped.
o Data Forwarding: When a source node has many packets,
it broadcasts PING packet to search for suitable delay in neighboring
nodes. If the packet pairs>1 then packets are transmitted otherwise
dropped. Simulation-based results demonstrate that CARP protocol is
best in PDR, Delay, and minimizes energy as compared to FBR and
EFlood protocols.
• 6LoWPAN: Low power Wireless Personal Area Network (6LoWPAN)
is regarded as one of the most important network layer encapsulation
protocol on which different types of IoT communications can be done
(Gomes et al., 2018). It encapsulates IPv6 long headers in IEEE 802.15.4
small data size packets of max size of 127 bytes. 6LoWPAN protocol
was designed in 2007 by IETF 6LoWPAN working group. It is primarily
responsible for performing re-ordering and fragmenting of IPv6 packets,
compressing protocol stack headers, enabling stateless addressing and
creating mesh routing to maintain efficient consistency with packet trans-
mission to upper layers. Considering IoT, 6LoWPAN is highly efficient
in terms of supporting different length addresses, efficient bandwidth,
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topologies, i.e., Star or Mesh, low power utilization, low cost, scalability,
mobility, and wakeup mode.6LoWPAN has four types of headers: No
6LoWPAN (00); Dispatch (01); Mesh-Addressing (10); Fragmentation
(11).
• 6Lo: In 2013, IPv6 over networks of resource-constrained nodes
(6Lo) Working Group proposed 6Lo (Yushev et al., 2016). Even though
two dierent protocols were developed, i.e., 6LoWPAN and 6TiSCH
based on IEEE 802.15.4 and IEEE 802.15.4e, but still more data links
are required, so 6Lo was proposed.6Lo denes the specications for IPv6
over constrained networks as follows:
o Limitations in terms of memory, power, and processing
capabilities.
o Energy Optimization and ecient bandwidth utilization.
o Hard upper bounds on the state, code space, and processing cycles.
o Missing of some Layer 2 services like connectivity and Broadcast.
The 6Lo has produced many standards like IPv6-Over-BLE, IPv6-
Over – Z-Wave and many are in progress like IPv6-over-DECT Ultra
Low Energy, IPv6-over-BACNET Master-Slave/Token-Passing networks,
IPv6-over-NFC, IPv6 over IEEE 802.11 AH, IPv6 over WIA-PA (Wireless
networks for Industrial Automation-Process Automation).
• 6TiSCH: IETF, new working group was formulated in November
2013 to allow IPv6 to pass through a Time Slotted Channel Hopping
(TSCH) mode of IEEE 802.15.4E data links (Dujovne et al., 2014). It
proposes a new concept called “Channel Distribution Usage (CDU)”
which is regarded as a matrix of cells comprising of frequencies available
in columns and time slots available for all sorts of network scheduling
operations in rows. 6TiSCH is regarded as novel solution for MESH type
networks that makes use of deterministic slotted channels to avoid all
sorts of attenuations, collisions, optimize energy consumption and main-
tain load balancing of data. It was designed to provide ecient delivery
and reduce jitter and latency in WSN networks like WirelessHART and
ISA 100.11a. 6TiSCH makes use of “On-The-Fly (OTF) Scheduling” in
which every node keeps a close eye on the packet transmission queue.
If the queue gets lled up, OTF determines that there is not enough
outbound bandwidth and res additional timeslots with neighboring
nodes. It supports dierent scheduling approaches like-Distributed,
Centralized, and Hybrid.
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• Message Queuing Telemetry Transport (MQTT): MQTT was
outlined by IBM in 1999 and is ISO Standard: ISO/IEC PRF 20922
publish-subscribe based messaging protocol (Light, 2017). It was designed
to connect all sorts of embedded devices and networks with middleware
and applications by using TCP protocol for transport layer. MQTT is highly
simple to implement and very suitable for those devices having limited
bandwidth and operate under unreliable network. MQTT protocol is advan-
tageous in terms of throughput, but lacks latency. MQTT protocol is highly
successful for implementation, where system has three main components:
Publishers, Subscribers, and Brokers. Considering IoT, publishers are
defined as “Sensors” connected to all brokers to transmit the data and go to
sleep mode, when not in action. Subscribers are termed as “Applications”
or “Sensor Data” to connect to brokers to inform when at any point of time
new data is available. The brokers perform the task of data classification and
send to subscribers according to their requirements (Figure 6.8).
FIGURE 6.8 MQTT architecture.
(Source: Jabby, (2014). MQTT and CoAP, IoT Protocols. Retrieved from: https://www.
eclipse.org/community/eclipse_newsletter/2014/february/article2.php.)
MQTT has three QoS levels:
o Fire and Forget: Transmit the message and forget about it, i.e.,
No receipt of acknowledgment of any message transmitted from
source to the destination device.
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o Delivered at Least Once: Message is delivered at least once for
every delivery and acknowledgement is sent to the source device.
o Delivery Exactly Once: In order to assure that the message is
delivered to the destination node, 4-way handshake procedure is
applied (Figure 6.9).
FIGURE 6.9 MQTT message format.
(Source: Living Mobile, (2015). MQTT Message Format. Retrieved from: http://
ritzinmobileworld.blogspot.com/2015/05/mqtt-message-format-part-i.html)
It consists of xed message header variable header and payload. Header
comprise of 4 bytes, length is 1–4 bytes.
• Secure MQTT (SMQTT): SMQTT (Secure MQTT) is regarded
as an extension of MQTT protocol, which combing standardized MQTT
with lightweight Attribute-Based Encryption (ABE) over elliptic curves
(Singh et al., 2015). The main reason behind adapting ABE algorithm is
because of its unique design which broadcasts encryption and with one
encryption a single message can be transferred to multiple users. SMQTT
protocol inherits security features via addition of new MQTT publish
message ‘Spublish’ with reserved message type ‘0000.’SMQTT has three
main entities:
o Publisher Device: Performs the task of publishing the data under
given topic.
o Subscriber Device: Receives data under same topic via broker.
o PKG or Broker: Third-party highly trusted.
SMQTT works in four main stages:
o Setup Phase: In this, all devices (Publisher and Subscriber)
register with PKG by giving a UNIQUE ID along with associ-
ated attributes. The master Secret Keyset is generated by PKG as
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per CP/KP-ABE scheme and all parameters are published with a
universal set.
o Encrypt Phase: As soon as data is published, it gets encrypted,
published by broker which sends the data to the subscribers and
data gets decrypted at the subscriber end using same master secret
key. Broker transmits SUBACK to all receiving devices.
o Publish Phase: All the encrypted data is embedded as Payload
by publisher in SPublish command and the SPublish packet is
transmitted back to Broker. It’s the duty of the broker to respond
to PUBACK Packet. Publisher on receiving PUBACK acknowl-
edges with reply by transmitting PUBREL packet. Broker then
broadcasts the message to all subscribers and deletes the data and
transmits PUBCOMP packet to sender.
o Decrypt Phase: The message is decrypted using private attribute
keys by verifying whether the access policy is satised or not.
• XMPP (Extensible Messaging and Presence Protocol):
Extensible Messaging and Presence Protocol (XMPP) is an XML based
communication protocol for message-oriented middleware (Ozturk, 2010;
Saint-Andre, 2011). The protocol was outlined by Jabber Open source
community in 1999 for maintaining contact list, presence information,
and real-time instant messaging and was named “Jabber.” It was later
standardized by IETF in 2002 by creating XMPP working group. XMPP
utilizes XML text format for facilitating person-to-person communication
and unlike MQTT, it runs over TCP. Considering IoT, XMPP facilitates
device addressing in a highly simple way. XMPP supports both architec-
tures: Publish/Subscribe and Request/Response, facilitating developers
with enough exibility and scalability to choose the required architecture.
XMPP gives a system for messaging over a network, which encourages
tons of applications as compared to conventional messaging and data
dispersion (Figure 6.10). The following are the key XMPP technologies:
o Core: Information with regard to core XMPP technologies for
XML streaming.
o Jingle: SIP compatible multimedia signaling for le transfer,
video, voice, and other applications.
o Multi-User Chat: Flexible, multi-party communications.
o PubSub: All sorts of alerts and real-time notications with regard
to data synchronization, etc.
o BOSH: An HTTP binding for XMPP trac.
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FIGURE 6.10 XMPP protocol – working.
(Source: rfwireless World, (2018). XMPP. Retrieved from: http://www.rfwireless-world.
com/IoT/XMPP-protocol.html.)
• CoAP (Constrained Application Protocol): CoAP was proposed
by the IETF and is regarded as a service layer protocol designed for utili-
zation in resource-constrained internet devices like WSN sensor nodes
(Shelby et al., 2014; Jan et al., 2016; Bormann et al., 2012, 2018; CoAP,
2016). CoAP supports easy translation to HTTP for simple integration with
web and also provides specialized requirements in terms of less overhead,
multicasting support, simplicity towards implementation. The protocol
provides lightweight RESTful (HTTP) interface which acts as a standard
interface between HTTP client and servers. The protocol is planned to
encourage Machine-to-Machine (M2M) applications like smart energy
and smart building, automation, etc. CoAP utilizes two types of messages:
Requests and Responses via simple, binary, and base header format. In
terms of security, CoAP utilizes UDP protocol as default and also supports
DTLS for high-level communication security for message exchange.
CoAP is sub-divided into two layers: Message Sub-layer and Request/
Response sub-layer. The message layer performs the task of reliable end
to end transfer of messages between nodes and the other layer deals with
all sorts of REST communications. It incorporates a CoAP Version (V),
Transaction Type (T), OC (Option Count), Code, and Message ID (M ID)
in the header, and rest it contains Token, Options, and Payload (Figure
6.11).
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FIGURE 6.11 CoAP protocol message format.
(Source: Shelby, Z., Hartke, K., Bormann, C. (2014). The Constrained Application Protocol
(CoAP). Internet Engineering Task Force (IETF). : https://tools.ietf.org/html/rfc7252)
CoAP protocol has four messaging modes:
o ConrmableMessage(CON): It requires a response, i.e., Posi-
tive or Negative Acknowledgement. In case of non-receipt of any
acknowledgment, retransmissions are done till all attempts are
done. Retransmissions make use of non-linear and exponential
strategy between attempts.
o Non-Conrmable Message (NON): It doesn’t require any sort
of Acknowledgement, but the message requires Message ID for
supervising in case of retransmission. If the message fails to be
processed at the recipient side, server responds with RST.
o Piggy-Backed: It is used for Client/Server communication,
when the server responds directly to the client after receiving the
message, i.e., Acknowledgement message for successful receipt
of the message. ACK message also contain response message, for
failure response, ACK contains failure response code.
o Separate Response: It is only used when the response from the
server comes in a message entirely dierent from acknowledg-
ment and server takes some time to transmit the message.
CoAP protocol makes use of dierent messages: GET, PUT, PUSH,
DELETE to perform operations like create, update, select, and delete.
• AMQP (Advanced Message Queuing Protocol): AMQP is
another open standard protocol for IoT typically designed for message-
oriented environments (Vinoski, 2006; Naik, 2017; Luzuriaga et al.,
2015). AMQP supports reliable communication via directives in terms of
at-most-once, at-least-once and exactly once-delivery. Unlike MQTT, it
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makes use of TCP for message exchange. In AMQP protocol, all types of
exchanges are handled by two main components: Exchanges and message
queues (Figure 6.12).
FIGURE 6.12 AMQP protocol working.
(Source: Electronics for You, (2018). AMQP. Retrieved from: https://iot.electronicsforu.
com/research-articles/internet-things-protocols-landscape/2/.)
The exchanges perform the task of message routing and all messages
are stored in message queue before they are routed to the receiver. It is
mostly found in business messaging. It denes “devices” as mobile units
communicating at back-end data centers.
• DDS (Data Distribution Service): This was proposed by Object
Management Group (OMG) for facilitating Machine to Machine commu-
nication and is regarded as yet another publishes/subscribes protocol
(Pardo-Castellote et al., 2005). Unlike MQTT, AMQP, and XMPP, DDS is
a highly reliable and secured protocol as it makes use of SSL and DTLS.
DDS has two levels of Interfaces-
o Data-Centric Publish-Subscribe (DCPS): DCPS, whose main
task is to assure ecient delivery of information to the designated
receivers.
o Data-Local Reconstruction Layer (DLRL): DLRL, which
facilitates easy integration with application layer.
DDS has 23 dierent levels of QoS like Security, Urgency, Priority,
Durability, Reliability, etc.
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6.4.2 SIMULATION TOOLS FOR IOT-INTERNET OF THINGS
In order to implement newly designed protocols and IoT devices in real-
time, everything has to undergo a thorough stage of evaluation and testing
to determine the required capability and performance of the protocol and
device. The testing and evaluation is carried out by the variety of simula-
tion tools. Example: Testing a large number of IoT nodes is not practical
in the real world during the initial stages of design and exploration because
of financial and operational constraints, especially when the protocol reli-
ability, security, and utility are unknown. So, to overcome all these chal-
lenges, a Simulation tool is the only way out. A standardized research in
IoT starts with idea formulation and ends with real-world implementation
comprising both virtual and real entities. In order to test virtual entities,
a simulation and testbed is essential, but for real-world live scenarios are
required for final testing before launching it finally for the end-user.
In this section of the chapter, we explore some simulators especially
designed for IoT which can lay a strong foundation for researchers to
perform novel research, propose novel designs cum architectures and
protocols to extend IoT technology.
• Bevywise IoT Simulator: It is free IoT simulation suite which
facilitates researchers to design, test, and emulate real-time IoT Devices,
middleware, and management solutions (Bevywise, 2018). The simulator
can simulate few to thousands of IoT devices under single box. It facili-
tates simulation of Smart Buildings, Smart Cities, Smart Manufacturing,
Smart Farming, Healthcare devices and many more. Features:
o Simple and Intuitive GUI Interface for easy operations.
o Fully support MQTT protocol.
o Powerful Python programming support to program user-custom-
ized messages for real-time transmission.
o Support for WILL topic and retain messages.
o REST-based APT for full simulation integration.
o Highly scalable, robust, and throughput oriented.
• IoTIFY: It is a cloud-based simulation platform for IoT facilitating
the user to design production-ready IoT and blockchain in web browser
(IoTIFY, 2018). It facilitates the user to design and develop powerful
simulations with regard to blockchain wallets, autonomous vehicles, smart
cities, smart meters, smart hospitals and many more.
Features:
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o Easy design of IoT device models using JavaScript-based
templates.
o Directs the virtual IoT devices to all types of cloud-Amazon AWS,
Azure, IBM Bluemix, and Google Cloud.
o Supports tons of protocols-MQTT, CoAP, UDP, TCP, DTLS, TLS,
HTTP, etc.
o Facilitates generation of specic tokens based for devices for
performing all sorts of registration and provisioning.
o Facilitates users to perform research on tons of varied network
conditions to determine throughput and latency.
• CupCarbon U-One: CupCarbon is a discrete wireless sensor
network and IoT simulator, which is multi-agent and performs geoloca-
tions-based simulations (CupCarbon, 2017; Mehdi et al., 2014). It enables
to users to run simulations and keep close eye on varied events changing
over time. It is well-facilitated simulator for IoT and can simulate smart
cities along with Unmanned Aerial Vehicles (UAVs) and detailed street-
level topology and maps belonging to real-world. It oers users to create
paths, open or congested roads and agent’s assignments to make them
mobile. Trajectories are generated in two ways: Manual or Automatic.
Cup carbon simulator has for modules:
o Agent Module: Includes devices and events to simulate WSN and
congure simulator for performing simulations.
o OpenStreetMap: Deploying wireless sensors on the map.
o WiSen Simulator Module: Simulate WSN and connected to all
agents of the simulator.
o Solver Module: Integrates all sorts of algorithms like Routing,
Coverage, etc.
Features:
o Interactive and highly simple GUI interface for users to perform
all sorts of simulations based on JavaFX.
o Simple script language based on SenScript which also facilitates
interactive commands.
o 2D/3D Visualization with OpenStreetMap.
o Facilitates Automation and repeated tasks using CupCarbon
Scripts.
o Arduino/XBee code generation.
o Integrates various radio modules and standards like 802.15.4,
ZigBee, Wi-Fi, and LoRa.
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o Intelligent Mobility models for running comprehensive
simulations.
• SimpleIoTSimulator: It creates a powerful and highly interac-
tive work environment for end-users to simulate hundreds or thousands
of sensors and gateways on a single computer (SimpleSoft, 2018). The
simulator supports tons of common IoT protocols like HTTP, HTTPS,
MQTT, MQTT-SN, CoAP, etc. The simulator can easily adapt to changing
customer requirements and create powerful replica of real-time scenarios.
The simulator supports both IPv4 and IPv6 protocols to simulating sensors
in constrained environments. Features are:
o Built-in learner utilities to make SimpleIoTSimulator to learn
more IoT scenarios.
o Powerful enough to simulate thousands of sensor nodes and gate-
ways to single simulator.
o Easy generation of user-based scripts to generate real-time
scenarios, modications, and dynamic changing properties.
o Realistic simulations with easy to use GUI interface.
o Supports almost every IoT standard protocol along with IPv4 and
IPv6.
o Supports other management protocols like SNMP, Telnet, SSH,
etc.
o Real-time sensor data modications as per changing operational
scenarios.
• MIMIC IoT Simulator: MIMIC IoT simulator provides a strong
real-world replica of operational test environment for managing all types
of IoT based sensors, gateways, and devices to test the IoT environment
(Gambit Communications, 2018). The simulator is fully competent to
simulate various scenarios like: Industry 4.0, Smart Factories, Smart
Cities and Agriculture. It is regarded as fully loaded simulator and bundles
almost types of applications, Middleware’s, Brokers, Load Balancers,
MQTT gateways and clients. MIMIC IoT Simulator has the following
main components:
o MQTT Simulator: It is fully equipped to simulate almost
1,00,000 MQTT v3.1 and MQTT 3.1.1 based sensors and devices.
Every device has a unique IP Address, Port, and Address. Once
the simulation scenario is created and started, every device can
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respond to all sorts of MQTT requests to and fro from a broker or
application from the network.
o HTTP/REST Simulator: All the sensors can communicate using
HTTP/HTTPS/REST. Every device is fully ecient to respond to
REST requests to any application from anywhere in work.
o CoAP Simulator: MIMIC can simulate tons of CoAP enabled
devices managed by one or more clients.
o Modbus Simulator: It facilitates the creation of Modbus slave
devices to communicate with Modbus Master Server using TCP
protocol. Every slave has a unique IP address that can request to
server and respond accordingly.
o MIMIC Shell: Main controller of all activities of MIMIC
commands using commands and even equipped with GUI
interface.
In addition to above, MIMIC also allows the users to simulate SNMP
v1, SNMPv2c, SNMPv3, NetFlow, sFlow, IPMI, Cisco IOS, Juniper
JUNOS, Telnet/SSH based devices.
Features:
o Facilitates creation of dynamic scenarios of Smart Cities, Industry
4.0 and other IoT based environments.
o Tons of IoT sensors can be simulated with an almost exact replica
of real-world.
o Facilitates reliable testing and scalability of sensors.
o Handles all sorts of connections and scenarios with regard to
heterogeneous environments.
• Cooja: It is regarded as Contiki network emulator-An exten-
sible Java-based simulator for emulating Tmote Sky and other nodes
(Mehmood, 2017; Nayyar and Singh, 2015; Thiruveedula, 2017; Bagula
and Erasmus, 2015). It is basically an operating system for simulating
resource-constrained and networked low-power IoT devices. It facilitates
multitasking and contains a fully equipped TCP/IP suite. It consists of a
powerful built-in suite for simulating and constructing powerful network
scenarios. Contiki supports IPv4; IPv6 along with various IoT based
protocols like: 6LoWPAN, RPL, CoAP. Cooja supports three dierent
levels of simulation -
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• Networking/Application Level: Cooja facilitates the users
to exchange all sorts of simulator modules like device drivers or radio
medium modules.
• Operating System Level: Cooja simulates OS via execution of
native operating system code. All sorts of user processes are executed to
alter Contiki core functionality.
• Machine Code Instruction Set Level: It facilitates new nodes
creation under varied structures as compared to standard nodes.
Features:
o Highly memory ecient and contains a dened set of mechanisms
for memory allocation like Memory block allocation memb,
managed memory allocator mmem, and C memory allocator
malloc.
o Fully operational IP network stack with almost all standard proto-
cols of networks TCP, UDP, and HTTP along with IoT protocol
stack.
o Fully support low-power devices simulation and gives a precision
estimation of nodes power utilization.
o Fully support dynamic loading and modules linking at simulation
run-time. The module load faster and link standard ELF les.
o Supports platforms like 8051, MSP430, ARM, and AVR devices.
o Supports commands via optional shell.
6.5 CONCLUSION
In view of the above arguments that support an exclusive discussion on IoT
and Digital Business Environment inclusive Cyber Space, Cyber Crimes
and Cybersecurity paradigm. Even though there was evidence of such
increased concerns about the cybercrime, cyber threat, risk approaching
from cyberspace along with the idea of serious cyberattacks from time to
time against decisive infrastructure perceived by top-notch agencies glob-
ally in digital business. Regarding social and sustainable business, positive
benefits from cyberspace are essential under ethical circumstances and
codes; however, acknowledges the threats related to cyberspace. More-
over, it highlights cyber world importance, even though more concerned is
still focused on connecting the opportunities connected to cyberspace and
minimizes the threats in today’s competitive world.
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KEYWORDS
•cybersecurity
•digital business environment
•internet of things (IoT)
•IoT protocols
•IoT security
•message queuing telemetry transport (MQTT)
•simulation tools
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